14 citations · 20 across the 5 of their papers we have counts for
3 papers · 1 filter
History repeats Itself: A Baseline for Temporal Knowledge Graph Forecasting
Julia Gastinger, Christian Meilicke, Federico Errica +3
Temporal Knowledge Graph (TKG) Forecasting aims at predicting links in Knowledge Graphs for future timesteps based on a history of Knowledge Graphs. To this day, standardized evalu…
ProcK: Machine Learning for Knowledge-Intensive Processes
Tobias Jacobs, Jingyi Yu, Julia Gastinger +1
We present a novel methodology to build powerful predictive process models. Our method, denoted ProcK (Process & Knowledge), relies not only on sequential input data in the form of…
Explaining Neural Matrix Factorization with Gradient Rollback
Carolin Lawrence, Timo Sztyler, Mathias Niepert
Explaining the predictions of neural black-box models is an important problem, especially when such models are used in applications where user trust is crucial. Estimating the infl…